fanasina/y_project
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Add some MACRO in neuron_t and debug deepQlearning

Browse Source
This commit is contained in:
fanasina
2024-07-09 17:38:58 +02:00
parent 824396f901
commit 0c9813beca
8 changed files with 810 additions and 85 deletions
Download Patch File Download Diff File Expand all files Collapse all files
deepQlearn_0/test/is_good.c
+645 -23
View File
@@ -253,6 +253,137 @@ TEST(circle_path_vehicle){
free_vehicle(vhcl);
}
TEST(circle_path_vehicle_00){
size_t nb_block = 7;
size_t dim= 2;
struct blocks * path = create_blocks(nb_block, dim);
copy_coordinate(path->lower_bound_block[0], (float[]){0,300});
copy_coordinate(path->upper_bound_block[0], (float[]){400,700});
copy_coordinate(path->lower_bound_block[1], (float[]){100,0});
copy_coordinate(path->upper_bound_block[1], (float[]){1000,300});
copy_coordinate(path->lower_bound_block[2], (float[]){1000,50});
copy_coordinate(path->upper_bound_block[2], (float[]){1400,500});
copy_coordinate(path->lower_bound_block[3], (float[]){1400,200});
copy_coordinate(path->upper_bound_block[3], (float[]){1800,700});
copy_coordinate(path->lower_bound_block[4], (float[]){1100,700});
copy_coordinate(path->upper_bound_block[4], (float[]){1700,1000});
copy_coordinate(path->lower_bound_block[5], (float[]){800,600});
copy_coordinate(path->upper_bound_block[5], (float[]){1100,975});
copy_coordinate(path->lower_bound_block[6], (float[]){100,700});
copy_coordinate(path->upper_bound_block[6], (float[]){800,975});
update_bounds_limits_blocks(path);
struct vehicle *vhcl = create_vehicle(path);
print_vehicle_n_path(vhcl, 20,40);
step_vehicle(vhcl, CENTER);
Sleep(200);
/* print_vehicle_n_path(vhcl, 0.2,0.4);
step_vehicle(vhcl, CENTER);
Sleep(200);
print_vehicle_n_path(vhcl, 0.2,0.4);
step_vehicle(vhcl, CENTER);
Sleep(200);
print_vehicle_n_path(vhcl, 0.2,0.4);
step_vehicle(vhcl, CENTER);
Sleep(200);
print_vehicle_n_path(vhcl, 0.2,0.4);
*/
free_vehicle(vhcl);
}
TEST(circle_path_vehicle_50){
size_t nb_block = 7;
size_t dim= 2;
struct blocks * path = create_blocks(nb_block, dim);
#if 1
copy_coordinate(path->lower_bound_block[6], (float[]){0,30});
copy_coordinate(path->upper_bound_block[6], (float[]){150,250});
copy_coordinate(path->lower_bound_block[5], (float[]){150,0});
copy_coordinate(path->upper_bound_block[5], (float[]){250,80});
copy_coordinate(path->lower_bound_block[4], (float[]){250,20});
copy_coordinate(path->upper_bound_block[4], (float[]){360,120});
copy_coordinate(path->lower_bound_block[3], (float[]){360,80});
copy_coordinate(path->upper_bound_block[3], (float[]){600,150});
copy_coordinate(path->lower_bound_block[2], (float[]){600,90});
copy_coordinate(path->upper_bound_block[2], (float[]){760,300});
copy_coordinate(path->lower_bound_block[1], (float[]){300,300});
copy_coordinate(path->upper_bound_block[1], (float[]){760,350});
copy_coordinate(path->lower_bound_block[0], (float[]){0,250});
copy_coordinate(path->upper_bound_block[0], (float[]){410,300});
#else
copy_coordinate(path->lower_bound_block[0], (float[]){0,0});
copy_coordinate(path->upper_bound_block[0], (float[]){150,250});
copy_coordinate(path->lower_bound_block[1], (float[]){150,0});
copy_coordinate(path->upper_bound_block[1], (float[]){250,150});
copy_coordinate(path->lower_bound_block[2], (float[]){250,80});
copy_coordinate(path->upper_bound_block[2], (float[]){360,200});
copy_coordinate(path->lower_bound_block[3], (float[]){360,70});
copy_coordinate(path->upper_bound_block[3], (float[]){600,170});
copy_coordinate(path->lower_bound_block[4], (float[]){600,90});
copy_coordinate(path->upper_bound_block[4], (float[]){760,300});
copy_coordinate(path->lower_bound_block[5], (float[]){300,300});
copy_coordinate(path->upper_bound_block[5], (float[]){760,350});
copy_coordinate(path->lower_bound_block[6], (float[]){0,250});
copy_coordinate(path->upper_bound_block[6], (float[]){410,300});
copy_coordinate(path->lower_bound_block[0], (float[]){0,0});
copy_coordinate(path->upper_bound_block[0], (float[]){100,250});
copy_coordinate(path->lower_bound_block[1], (float[]){100,0});
copy_coordinate(path->upper_bound_block[1], (float[]){250,80});
copy_coordinate(path->lower_bound_block[2], (float[]){250,0});
copy_coordinate(path->upper_bound_block[2], (float[]){360,140});
copy_coordinate(path->lower_bound_block[3], (float[]){360,70});
copy_coordinate(path->upper_bound_block[3], (float[]){600,140});
copy_coordinate(path->lower_bound_block[4], (float[]){600,90});
copy_coordinate(path->upper_bound_block[4], (float[]){720,300});
copy_coordinate(path->lower_bound_block[5], (float[]){300,300});
copy_coordinate(path->upper_bound_block[5], (float[]){720,350});
copy_coordinate(path->lower_bound_block[6], (float[]){0,250});
copy_coordinate(path->upper_bound_block[6], (float[]){410,300});
#endif
update_bounds_limits_blocks(path);
struct vehicle *vhcl = create_vehicle(path);
print_vehicle_n_path(vhcl, 10,10);
step_vehicle(vhcl, CENTER);
Sleep(200);
/* print_vehicle_n_path(vhcl, 0.2,0.4);
step_vehicle(vhcl, CENTER);
Sleep(200);
print_vehicle_n_path(vhcl, 0.2,0.4);
step_vehicle(vhcl, CENTER);
Sleep(200);
print_vehicle_n_path(vhcl, 0.2,0.4);
step_vehicle(vhcl, CENTER);
Sleep(200);
print_vehicle_n_path(vhcl, 0.2,0.4);
*/
free_vehicle(vhcl);
}
TEST(reward_list){
@@ -261,8 +392,125 @@ TEST(reward_list){
free_status_qlearning(l_reward);
}
float f(float x){
return 1/(1+exp((double)(-x)));
}
float df(float x){
return exp(-x)/ ((1+exp(-x)) * (1+exp(-x)));
}
#if 1
TEST(first_learn_vehicle){
TEST(first_learn_vehicle_rev50){
size_t nb_block = 7;
size_t dim= 2;
struct blocks * path = create_blocks(nb_block, dim);
#if 0
copy_coordinate(path->lower_bound_block[6], (float[]){0,30});
copy_coordinate(path->upper_bound_block[6], (float[]){150,250});
copy_coordinate(path->lower_bound_block[5], (float[]){150,0});
copy_coordinate(path->upper_bound_block[5], (float[]){250,80});
copy_coordinate(path->lower_bound_block[4], (float[]){250,20});
copy_coordinate(path->upper_bound_block[4], (float[]){360,120});
copy_coordinate(path->lower_bound_block[3], (float[]){360,80});
copy_coordinate(path->upper_bound_block[3], (float[]){600,150});
copy_coordinate(path->lower_bound_block[2], (float[]){600,90});
copy_coordinate(path->upper_bound_block[2], (float[]){760,300});
copy_coordinate(path->lower_bound_block[1], (float[]){300,300});
copy_coordinate(path->upper_bound_block[1], (float[]){760,350});
copy_coordinate(path->lower_bound_block[0], (float[]){0,250});
copy_coordinate(path->upper_bound_block[0], (float[]){410,300});
#else
copy_coordinate(path->lower_bound_block[4], (float[]){0,0});
copy_coordinate(path->upper_bound_block[4], (float[]){150,250});
copy_coordinate(path->lower_bound_block[5], (float[]){150,40});
copy_coordinate(path->upper_bound_block[5], (float[]){250,150});
copy_coordinate(path->lower_bound_block[6], (float[]){250,80});
copy_coordinate(path->upper_bound_block[6], (float[]){360,200});
copy_coordinate(path->lower_bound_block[0], (float[]){360,70});
copy_coordinate(path->upper_bound_block[0], (float[]){600,150});
copy_coordinate(path->lower_bound_block[1], (float[]){600,90});
copy_coordinate(path->upper_bound_block[1], (float[]){760,300});
copy_coordinate(path->lower_bound_block[2], (float[]){260,300});
copy_coordinate(path->upper_bound_block[2], (float[]){760,360});
copy_coordinate(path->lower_bound_block[3], (float[]){0,250});
copy_coordinate(path->upper_bound_block[3], (float[]){410,300});
#endif
update_bounds_limits_blocks(path);
struct vehicle *car = create_vehicle(path);
config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,24,24,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
//config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,14,14,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
bool randomize=true;
float minR = -0.5, maxR = 0.5;
int randomRange = 500;
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.001;
struct networks_qlearning *nnetworks = create_nework_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
learning_rate
);
struct status_qlearning *qlstatus = create_status_qlearning ();
struct delay_params *dly = create_delay_params (
100/*size_t delay_between_episodes*/,
10/*size_t delay_between_games*/
);
struct qlearning_params *qlparams = create_qlearning_params (
0.95/*float gamma*/,
learning_rate,
0 /* (not used!)float discount_factor*/,
0.99 /*float exploration_factor*/,
20/*long int nb_training_before_update_weight_in_target*/,
10000/*size_t number_episodes*/
);
/* UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, f_act, f );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, f_act , f );
*/
struct print_params *pprint = create_print_params(
12/*float scale_x*/,12 /*float scale_y*/,
dly/*struct delay_params * dly_p*/
);
struct RL_agent *rlAgent = create_RL_agent (
nnetworks /*struct networks_qlearning * networks*/,
car /*struct vehicle * car*/,
qlstatus /*struct status_qlearning * status*/,
pprint /*struct print_params * pprint*/,
qlparams/*struct qlearning_params *qlearnParams*/
);
learn_to_drive(rlAgent);
free_RL_agent(rlAgent);
}
#endif
#if 1
TEST(first_learn_vehicle_50){
size_t nb_block = 7;
size_t dim= 2;
struct blocks * path = create_blocks(nb_block, dim);
@@ -270,6 +518,59 @@ TEST(first_learn_vehicle){
#if 1
copy_coordinate(path->lower_bound_block[0], (float[]){0,0});
copy_coordinate(path->upper_bound_block[0], (float[]){150,250});
copy_coordinate(path->lower_bound_block[1], (float[]){150,0});
copy_coordinate(path->upper_bound_block[1], (float[]){250,150});
copy_coordinate(path->lower_bound_block[2], (float[]){250,80});
copy_coordinate(path->upper_bound_block[2], (float[]){360,200});
copy_coordinate(path->lower_bound_block[3], (float[]){360,70});
copy_coordinate(path->upper_bound_block[3], (float[]){600,170});
copy_coordinate(path->lower_bound_block[4], (float[]){600,90});
copy_coordinate(path->upper_bound_block[4], (float[]){760,300});
copy_coordinate(path->lower_bound_block[5], (float[]){300,300});
copy_coordinate(path->upper_bound_block[5], (float[]){760,350});
copy_coordinate(path->lower_bound_block[6], (float[]){0,250});
copy_coordinate(path->upper_bound_block[6], (float[]){410,300});
/*
copy_coordinate(path->lower_bound_block[0], (float[]){0,0});
copy_coordinate(path->upper_bound_block[0], (float[]){100,250});
copy_coordinate(path->lower_bound_block[1], (float[]){100,0});
copy_coordinate(path->upper_bound_block[1], (float[]){250,80});
copy_coordinate(path->lower_bound_block[2], (float[]){250,0});
copy_coordinate(path->upper_bound_block[2], (float[]){360,140});
copy_coordinate(path->lower_bound_block[3], (float[]){360,70});
copy_coordinate(path->upper_bound_block[3], (float[]){600,140});
copy_coordinate(path->lower_bound_block[4], (float[]){600,90});
copy_coordinate(path->upper_bound_block[4], (float[]){720,300});
copy_coordinate(path->lower_bound_block[5], (float[]){300,300});
copy_coordinate(path->upper_bound_block[5], (float[]){720,350});
copy_coordinate(path->lower_bound_block[6], (float[]){0,250});
copy_coordinate(path->upper_bound_block[6], (float[]){410,300});
copy_coordinate(path->lower_bound_block[0], (float[]){0,300});
copy_coordinate(path->upper_bound_block[0], (float[]){400,700});
copy_coordinate(path->lower_bound_block[1], (float[]){100,0});
copy_coordinate(path->upper_bound_block[1], (float[]){1000,300});
copy_coordinate(path->lower_bound_block[2], (float[]){1000,50});
copy_coordinate(path->upper_bound_block[2], (float[]){1400,500});
copy_coordinate(path->lower_bound_block[3], (float[]){1400,200});
copy_coordinate(path->upper_bound_block[3], (float[]){1800,700});
copy_coordinate(path->lower_bound_block[4], (float[]){1100,700});
copy_coordinate(path->upper_bound_block[4], (float[]){1700,1000});
copy_coordinate(path->lower_bound_block[5], (float[]){800,600});
copy_coordinate(path->upper_bound_block[5], (float[]){1100,975});
copy_coordinate(path->lower_bound_block[6], (float[]){100,700});
copy_coordinate(path->upper_bound_block[6], (float[]){800,975});
*/
#else
copy_coordinate(path->lower_bound_block[0], (float[]){0,3});
copy_coordinate(path->upper_bound_block[0], (float[]){4,7});
copy_coordinate(path->lower_bound_block[1], (float[]){1,0});
@@ -285,23 +586,7 @@ TEST(first_learn_vehicle){
copy_coordinate(path->lower_bound_block[6], (float[]){1,7});
copy_coordinate(path->upper_bound_block[6], (float[]){8,9.75});
#else
copy_coordinate(path->lower_bound_block[0], (float[]){0,0});
copy_coordinate(path->upper_bound_block[0], (float[]){2,7});
copy_coordinate(path->lower_bound_block[1], (float[]){2,0});
copy_coordinate(path->upper_bound_block[1], (float[]){4,2});
copy_coordinate(path->lower_bound_block[2], (float[]){4,0.5});
copy_coordinate(path->upper_bound_block[2], (float[]){8,3});
copy_coordinate(path->lower_bound_block[3], (float[]){8,0});
copy_coordinate(path->upper_bound_block[3], (float[]){16,2});
copy_coordinate(path->lower_bound_block[4], (float[]){16,0});
copy_coordinate(path->upper_bound_block[4], (float[]){18,7});
copy_coordinate(path->lower_bound_block[5], (float[]){6,7});
copy_coordinate(path->upper_bound_block[5], (float[]){18,9});
copy_coordinate(path->lower_bound_block[6], (float[]){2,6});
copy_coordinate(path->upper_bound_block[6], (float[]){6,8});
#endif
update_bounds_limits_blocks(path);
@@ -309,9 +594,10 @@ TEST(first_learn_vehicle){
struct vehicle *car = create_vehicle(path);
config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,24,24,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
//config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,14,14,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
bool randomize=true;
float minR = 0, maxR = 1;
float minR = -0.5, maxR = 0.5;
int randomRange = 500;
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
@@ -325,20 +611,356 @@ TEST(first_learn_vehicle){
struct status_qlearning *qlstatus = create_status_qlearning ();
struct delay_params *dly = create_delay_params (
200/*size_t delay_between_episodes*/,
20/*size_t delay_between_games*/
100/*size_t delay_between_episodes*/,
10/*size_t delay_between_games*/
);
struct qlearning_params *qlparams = create_qlearning_params (
0.95/*float gamma*/,
learning_rate,
0 /* (not used!)float discount_factor*/,
0.99/*float exploration_factor*/,
0.99 /*float exploration_factor*/,
20/*long int nb_training_before_update_weight_in_target*/,
10000/*size_t number_episodes*/
);
/* UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, f_act, f );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, f_act , f );
*/
struct print_params *pprint = create_print_params(
0.2/*float scale_x*/,0.4 /*float scale_y*/,
12/*float scale_x*/,12 /*float scale_y*/,
dly/*struct delay_params * dly_p*/
);
struct RL_agent *rlAgent = create_RL_agent (
nnetworks /*struct networks_qlearning * networks*/,
car /*struct vehicle * car*/,
qlstatus /*struct status_qlearning * status*/,
pprint /*struct print_params * pprint*/,
qlparams/*struct qlearning_params *qlearnParams*/
);
learn_to_drive(rlAgent);
free_RL_agent(rlAgent);
}
#endif
#if 0
TEST(first_learn_vehicle){
size_t nb_block = 7;
size_t dim= 2;
struct blocks * path = create_blocks(nb_block, dim);
#if 1
copy_coordinate(path->lower_bound_block[0], (float[]){0,300});
copy_coordinate(path->upper_bound_block[0], (float[]){400,700});
copy_coordinate(path->lower_bound_block[1], (float[]){100,0});
copy_coordinate(path->upper_bound_block[1], (float[]){1000,300});
copy_coordinate(path->lower_bound_block[2], (float[]){1000,50});
copy_coordinate(path->upper_bound_block[2], (float[]){1400,500});
copy_coordinate(path->lower_bound_block[3], (float[]){1400,200});
copy_coordinate(path->upper_bound_block[3], (float[]){1800,700});
copy_coordinate(path->lower_bound_block[4], (float[]){1100,700});
copy_coordinate(path->upper_bound_block[4], (float[]){1700,1000});
copy_coordinate(path->lower_bound_block[5], (float[]){800,600});
copy_coordinate(path->upper_bound_block[5], (float[]){1100,975});
copy_coordinate(path->lower_bound_block[6], (float[]){100,700});
copy_coordinate(path->upper_bound_block[6], (float[]){800,975});
#else
copy_coordinate(path->lower_bound_block[0], (float[]){0,3});
copy_coordinate(path->upper_bound_block[0], (float[]){4,7});
copy_coordinate(path->lower_bound_block[1], (float[]){1,0});
copy_coordinate(path->upper_bound_block[1], (float[]){10,3});
copy_coordinate(path->lower_bound_block[2], (float[]){10,0.5});
copy_coordinate(path->upper_bound_block[2], (float[]){14,5});
copy_coordinate(path->lower_bound_block[3], (float[]){14,2});
copy_coordinate(path->upper_bound_block[3], (float[]){18,7});
copy_coordinate(path->lower_bound_block[4], (float[]){11,7});
copy_coordinate(path->upper_bound_block[4], (float[]){17,10});
copy_coordinate(path->lower_bound_block[5], (float[]){8,6});
copy_coordinate(path->upper_bound_block[5], (float[]){11,9.75});
copy_coordinate(path->lower_bound_block[6], (float[]){1,7});
copy_coordinate(path->upper_bound_block[6], (float[]){8,9.75});
#endif
update_bounds_limits_blocks(path);
struct vehicle *car = create_vehicle(path);
config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,24,24,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
//config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,14,14,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
bool randomize=true;
float minR = -0.5, maxR = 0.5;
int randomRange = 5000;
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.1;
struct networks_qlearning *nnetworks = create_nework_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
learning_rate
);
struct status_qlearning *qlstatus = create_status_qlearning ();
struct delay_params *dly = create_delay_params (
100/*size_t delay_between_episodes*/,
10/*size_t delay_between_games*/
);
struct qlearning_params *qlparams = create_qlearning_params (
0.95/*float gamma*/,
learning_rate,
0 /* (not used!)float discount_factor*/,
0.85 /*float exploration_factor*/,
20/*long int nb_training_before_update_weight_in_target*/,
10000/*size_t number_episodes*/
);
/* UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, f_act, f );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, f_act , f );
*/
struct print_params *pprint = create_print_params(
20/*float scale_x*/,40 /*float scale_y*/,
dly/*struct delay_params * dly_p*/
);
struct RL_agent *rlAgent = create_RL_agent (
nnetworks /*struct networks_qlearning * networks*/,
car /*struct vehicle * car*/,
qlstatus /*struct status_qlearning * status*/,
pprint /*struct print_params * pprint*/,
qlparams/*struct qlearning_params *qlearnParams*/
);
learn_to_drive(rlAgent);
free_RL_agent(rlAgent);
}
#endif
#if 0
TEST(first_learn_vehicle){
size_t nb_block = 7;
size_t dim= 2;
struct blocks * path = create_blocks(nb_block, dim);
#if 1
copy_coordinate(path->lower_bound_block[0], (float[]){0,300});
copy_coordinate(path->upper_bound_block[0], (float[]){400,700});
copy_coordinate(path->lower_bound_block[1], (float[]){100,0});
copy_coordinate(path->upper_bound_block[1], (float[]){1000,300});
copy_coordinate(path->lower_bound_block[2], (float[]){1000,50});
copy_coordinate(path->upper_bound_block[2], (float[]){1400,500});
copy_coordinate(path->lower_bound_block[3], (float[]){1400,200});
copy_coordinate(path->upper_bound_block[3], (float[]){1800,700});
copy_coordinate(path->lower_bound_block[4], (float[]){1100,700});
copy_coordinate(path->upper_bound_block[4], (float[]){1700,1000});
copy_coordinate(path->lower_bound_block[5], (float[]){800,600});
copy_coordinate(path->upper_bound_block[5], (float[]){1100,975});
copy_coordinate(path->lower_bound_block[6], (float[]){100,700});
copy_coordinate(path->upper_bound_block[6], (float[]){800,975});
#else
copy_coordinate(path->lower_bound_block[0], (float[]){0,3});
copy_coordinate(path->upper_bound_block[0], (float[]){4,7});
copy_coordinate(path->lower_bound_block[1], (float[]){1,0});
copy_coordinate(path->upper_bound_block[1], (float[]){10,3});
copy_coordinate(path->lower_bound_block[2], (float[]){10,0.5});
copy_coordinate(path->upper_bound_block[2], (float[]){14,5});
copy_coordinate(path->lower_bound_block[3], (float[]){14,2});
copy_coordinate(path->upper_bound_block[3], (float[]){18,7});
copy_coordinate(path->lower_bound_block[4], (float[]){11,7});
copy_coordinate(path->upper_bound_block[4], (float[]){17,10});
copy_coordinate(path->lower_bound_block[5], (float[]){8,6});
copy_coordinate(path->upper_bound_block[5], (float[]){11,9.75});
copy_coordinate(path->lower_bound_block[6], (float[]){1,7});
copy_coordinate(path->upper_bound_block[6], (float[]){8,9.75});
#endif
update_bounds_limits_blocks(path);
struct vehicle *car = create_vehicle(path);
config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,24,24,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
//config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,14,14,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
bool randomize=true;
float minR = -0.5, maxR = 0.5;
int randomRange = 5000;
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.1;
struct networks_qlearning *nnetworks = create_nework_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
learning_rate
);
struct status_qlearning *qlstatus = create_status_qlearning ();
struct delay_params *dly = create_delay_params (
100/*size_t delay_between_episodes*/,
10/*size_t delay_between_games*/
);
struct qlearning_params *qlparams = create_qlearning_params (
0.95/*float gamma*/,
learning_rate,
0 /* (not used!)float discount_factor*/,
0.85 /*float exploration_factor*/,
20/*long int nb_training_before_update_weight_in_target*/,
10000/*size_t number_episodes*/
);
/* UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, f_act, f );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, f_act , f );
*/
struct print_params *pprint = create_print_params(
20/*float scale_x*/,40 /*float scale_y*/,
dly/*struct delay_params * dly_p*/
);
struct RL_agent *rlAgent = create_RL_agent (
nnetworks /*struct networks_qlearning * networks*/,
car /*struct vehicle * car*/,
qlstatus /*struct status_qlearning * status*/,
pprint /*struct print_params * pprint*/,
qlparams/*struct qlearning_params *qlearnParams*/
);
learn_to_drive(rlAgent);
free_RL_agent(rlAgent);
}
#endif
#if 0
TEST(first_learn_vehicle){
size_t nb_block = 7;
size_t dim= 2;
struct blocks * path = create_blocks(nb_block, dim);
#if 1
copy_coordinate(path->lower_bound_block[0], (float[]){0,300});
copy_coordinate(path->upper_bound_block[0], (float[]){400,700});
copy_coordinate(path->lower_bound_block[1], (float[]){100,0});
copy_coordinate(path->upper_bound_block[1], (float[]){1000,300});
copy_coordinate(path->lower_bound_block[2], (float[]){1000,50});
copy_coordinate(path->upper_bound_block[2], (float[]){1400,500});
copy_coordinate(path->lower_bound_block[3], (float[]){1400,200});
copy_coordinate(path->upper_bound_block[3], (float[]){1800,700});
copy_coordinate(path->lower_bound_block[4], (float[]){1100,700});
copy_coordinate(path->upper_bound_block[4], (float[]){1700,1000});
copy_coordinate(path->lower_bound_block[5], (float[]){800,600});
copy_coordinate(path->upper_bound_block[5], (float[]){1100,975});
copy_coordinate(path->lower_bound_block[6], (float[]){100,700});
copy_coordinate(path->upper_bound_block[6], (float[]){800,975});
#else
copy_coordinate(path->lower_bound_block[0], (float[]){0,3});
copy_coordinate(path->upper_bound_block[0], (float[]){4,7});
copy_coordinate(path->lower_bound_block[1], (float[]){1,0});
copy_coordinate(path->upper_bound_block[1], (float[]){10,3});
copy_coordinate(path->lower_bound_block[2], (float[]){10,0.5});
copy_coordinate(path->upper_bound_block[2], (float[]){14,5});
copy_coordinate(path->lower_bound_block[3], (float[]){14,2});
copy_coordinate(path->upper_bound_block[3], (float[]){18,7});
copy_coordinate(path->lower_bound_block[4], (float[]){11,7});
copy_coordinate(path->upper_bound_block[4], (float[]){17,10});
copy_coordinate(path->lower_bound_block[5], (float[]){8,6});
copy_coordinate(path->upper_bound_block[5], (float[]){11,9.75});
copy_coordinate(path->lower_bound_block[6], (float[]){1,7});
copy_coordinate(path->upper_bound_block[6], (float[]){8,9.75});
#endif
update_bounds_limits_blocks(path);
struct vehicle *car = create_vehicle(path);
config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,24,24,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
//config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,14,14,3}); /* 3 input , 3 target; 2 hidden layer with 24 neurons each */
bool randomize=true;
float minR = -0.5, maxR = 0.5;
int randomRange = 5000;
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.1;
struct networks_qlearning *nnetworks = create_nework_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
learning_rate
);
struct status_qlearning *qlstatus = create_status_qlearning ();
struct delay_params *dly = create_delay_params (
100/*size_t delay_between_episodes*/,
10/*size_t delay_between_games*/
);
struct qlearning_params *qlparams = create_qlearning_params (
0.95/*float gamma*/,
learning_rate,
0 /* (not used!)float discount_factor*/,
0.85 /*float exploration_factor*/,
20/*long int nb_training_before_update_weight_in_target*/,
10000/*size_t number_episodes*/
);
/* UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->main_net, f_act, f );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, d_f_act , df );
UPDATE_ATTRIBUTE_NEURONE_IN_ALL_LAYERS(TYPE_FLOAT, nnetworks->target_net, f_act , f );
*/
struct print_params *pprint = create_print_params(
20/*float scale_x*/,40 /*float scale_y*/,
dly/*struct delay_params * dly_p*/
);